Trust Issues for Big Data about High-Value Manufactured Parts

Adhikari, Anku; Hojjati, Avesta; Shen, Juanli; Hsu, Jui‐Ting; King, William P.; Winslett, Marianne

doi:10.1109/bigdatasecurity-hpsc-ids.2016.50

Cited by 7 publications

(5 citation statements)

References 6 publications

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“…Supporting technologies for artificial intelligence include big data analytics, decision making, and natural language processing. The potential applications of big data analytics in analyzing the digital thread to enhance manufacturing processes and reduce costs are discussed in [105]. Through natural language processing techniques, textual data can be processed and understood, transforming them into system models while ensuring the accuracy, consistency, and completeness of the models.…”

Section: Enabling Lifecycle Lightweight Interaction Through Surrogate...mentioning

confidence: 99%

A Literature Review of the Digital Thread: Definition, Key Technologies, and Applications

Zhang,

Liu,

Chen

2024

Systems

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The digital thread, as a crucial technology for industrial digitization and the realization of smart manufacturing, has garnered extensive attention and research in recent years. Furthermore, there is a growing interest in the key technologies supporting the implementation of the digital thread. Given the diversity of product lifecycle models, various definitions, reference architectures, and implementation methods have been proposed to study the digital thread. Thus, this study systematically investigates the current definition, key technologies, and applications of the digital thread. A comprehensive analysis of 94 articles spanning from 2015 to 2023 was conducted, clarifying the definition of the digital thread and its relationship with related terms. Building upon this foundation, this study delves into the research methodologies concerning pivotal technologies in implementing the digital thread (such as authoritative sources of truth, data linkage, and model integration) and scrutinizes various application scenarios of the digital thread, providing a comprehensive summary. Finally, this study presents the research findings along with recommendations for future research endeavors.

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Section: Enabling Lifecycle Lightweight Interaction Through Surrogate...mentioning

confidence: 99%

A Literature Review of the Digital Thread: Definition, Key Technologies, and Applications

Zhang,

Liu,

Chen

2024

Systems

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“…Furthermore, the users do not know their critical data and their data security. That's why customers do not trust cloud computing services and prefer to store their critical data on their own IT system at home instead of the cloud 8,11,23,24,33,35 …”

Section: Literature Reviewmentioning

confidence: 99%

Identification and prioritization of security challenges of big data on cloud computing based on SLR: A fuzzy‐TOPSIS analysis approach

Khan

et al. 2021

J Software Evolu Process

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Nowadays, data is increasing exponentially, although cloud computing is an eminent approach for the organization, processing, and availability of data for organizational growth over the internet. Besides, a lot of advantages of cloud computing, yet it is suffered from security challenges, which affect big data while using cloud services on the internet. For this purpose, we conducted a detailed systematic literature review (SLR) study, to identify and capture the security challenges of big data on the cloud computing platform. Our research findings determine and develop a taxonomy, based on the prioritization of the security challenges of big data on cloud computing. We identified a total of 15 critical security challenges using the proposed SLR, with the frequency of each challenge >25%, and are further validated by the industrial specialists using a questionnaire survey study. The identified security challenges are data secrecy issue, geographical data location issue, unauthorized data access issue, lack of control, lack of data management, network‐level issues, data integrity issue, data recovery issue, lack of trust, data sharing issue, data availability, asset issues, legal amenabilities, lack of quality issues, and lack of consistency. The security challenges identified and captured through the SLR study are categorized into four levels, namely, steadiness, management, control, and eminence. Conclusively, we applied the fuzzy‐TOPSIS approach to prioritize and identify the significance of each identified security challenge for the big data usage on cloud computing. Based on our proposed approach, the “data secrecy issue” has been identified as the most prominent security challenge with the captured value of “0.765.” The fuzzy TOPSIS is an effective and innovative research approach in the field of computer science. It has been applied positively to other research areas to address and identify the fuzziness and uncertainty of multiple decision‐making glitches. The findings of the research paper will assist the software vendor organization when using the cloud platform for big data security. Also, using the proposed approach, software vendors can prioritize and analyze the uncertainty and ambiguousness among these security challenges.

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“…So that's why customer do not trust on cloud computing and refer to store their personal data on their own system at home instead of cloud environment [8,12,25,35,42,43]. Technical Network issue: In cloud computing data communication occur through unsecured network such as Internet, where every node can easily change data or inter node communication so that to breach the entire connection of the system [16,42,44,45]. Un-controlled access of Data: In cloud computing all the nodes are inter linked with each other for data processing.…”

Section: Introductionmentioning

confidence: 99%

Analyzing and Evaluating Critical Challenges and Practices for Software Vendor Organizations to Secure Big Data on Cloud Computing: An AHP-Based Systematic Approach

Khan

et al. 2021

IEEE Access

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Recently, its becomes easy to track down the data due to its availability in a large number. Although for data management, processing, and obtainability, cloud computing is considered a well-known approach for organizational development on the internet. Despite many advantages, cloud computing has still numerous security challenges that can affect the big-data usage on cloud computing. To find the security issues/challenges that are faced by software vendors' organizations we conducted a systematic literature review (SLR) through which we have find out 103 relevant research publications by developing a search string that is inspired by the research questions. This relevant data was comprised from different databases e.g. Google Scholar, IEEE Explore, ScienceDirect, ACM Digital Library, and SpringerLink. Furthermore, for the detailed literature review, we have accomplished all the steps in SLR, for example, development of SLR protocol, Initials and final assortment of the relevant data, data extraction, data quality assessment, and data synthesis. We identified fifteen (15) critical security challenges which are: data secrecy, geographical data location, unauthorized data access, lack of control, lack of data management, network-level issues, data integrity, data recovery, lack of trust, data sharing, data availability, asset issues, legal amenabilities, lack of quality, and lack of consistency. Furthermore, sixty four (64) standard practices are identified for these critical security challenges using the proposed SLR that could help vendor organizations to overcome the security challenges for big data. The findings of our research study demonstrate the resemblances and divergences in the identified security challenges in different periods, continents, databases, and methods. The proposed SLR will also support software vendor organizations for securing big data on the cloud computing platforms.

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Trust Issues for Big Data about High-Value Manufactured Parts

Cited by 7 publications

References 6 publications

A Literature Review of the Digital Thread: Definition, Key Technologies, and Applications

A Literature Review of the Digital Thread: Definition, Key Technologies, and Applications

Identification and prioritization of security challenges of big data on cloud computing based on SLR: A fuzzy‐TOPSIS analysis approach

Analyzing and Evaluating Critical Challenges and Practices for Software Vendor Organizations to Secure Big Data on Cloud Computing: An AHP-Based Systematic Approach

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